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Submitted on 11 Jul 2019
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Combined assessment of energy systems and urban planning to evaluate the long-term impact of urban
development
Matthieu Denoux, Edi Assoumou, Nadia Maïzi
To cite this version:
Matthieu Denoux, Edi Assoumou, Nadia Maïzi. Combined assessment of energy systems and urban planning to evaluate the long-term impact of urban development. Energy and Society in Transition: 2nd International Conference on Energy Research and Social Science, May 2019, Tempe, United States. 2019. �hal-02180948�
1. C
ITY
GROWTH
ISSUE
Matthieu DENOUX, Edi ASSOUMOU, Nadia MAÏZI
MINES ParisTech, PSL Research University, CMA - Centre de Mathématiques Appliquées
C
OMBINED
ASSESSMENT
OF
ENERGY
SYSTEMS
AND
URBAN
PLANNING
TO
EVALUATE
THE
LONG
-
TERM
IMPACT
OF
URBAN
DEVELOPMENT
4. U
RBAN
ARCHETYPES
3. U
RBAN
PLANNERS
’
KNOWLEDGE
5. L
AND
-
USE
OPTIMIZATION
MODEL
AND
RESULTS
Long-term
demographic evolution
Need for housing, jobs, infrastructure, public
facilities, etc.
Use data science, GIS, optimal and
prospective modelling to tackle long-term
impact of urban planning on the environment.
Table: « Cities’ Contribution to Climate Change », Worldbank, Washington D.C., 10, Dec. 2012.
from open data sources and repositories available for research (INSEE, IGN, Copernicus, Bordeaux, etc.) ANMA’s approach:
Name Concerns Description
Green Land use Green spaces must always remain, at least, at the base-year level.
Greener Land use Green spaces must expand to, at least, X %.
Towers Buildings Constrains the number of high towers that can be built every year as such building projects very often meet with opposition.
Artificial Land use Artificial ground must always remain, at most, at the base-year level.
Less artificial Land use Artificial ground must decrease, at most, by X %.
Double population Final demand Population, instead of following INSEE trends, must double before the end.
New way of life Land use & buildings
New ways of occupying the land from urban planners’ projects.
D
EMAND DRIVENPopulation rise generates: – Housing demand
– Job demand
– School demand – Mobility demand
Figure: INSEE demographic trend (blue) for Gironde department where Bordeaux is located against a
doubling evolution trend
Droite :
C:\Users\matthieu.denoux\ownCloud\Code\Graphisme\outputs\insee_trend.png
Milieu :
C:\Users\matthieu.denoux\ownCloud\Valorisation\2019-06-03_IEW\RES\iew_res.pptx
M
INIMIZES THE IMPACTSC
ONSTRAINED BYSeparated between: – Built surface
– Dedicated road – Natural land
– Other uses (can be converted)
– Specific areas (protected) – Political limits – Useable surface – Acceptability of towers – Green spaces – Energy performance – Access to public transportation
How cities can act:
- Concentrating population,
emissions, consumption;
- Transforming natural land; - Organizing human activity;
- Producing final demand (transportation, heating, food, etc.);
- Gathering flows;
- Being flexible;
- Cooperating internationally;
(e.g. BreatheLife Campaign, C40Cities, 100 Resilient Cities)
Changes in six areas—water, waste, food, energy, transportation, and land use—are needed to meet the challenge to
make cities and the vast areas they affect more viable. the city could align its
consumption with realistic needs, produce more of its own food and energy, and put much more of its waste to use.
[1]
M. O’Meara, « Reinventing cities for people and the planet »,
Worldwatch Paper, no 147, p. 4-94, 1999. Creation of scenarios – Retrofitting policy – Nature and artificial areas equilibrium – Growth levels – Transportation policies – Heat networks
Realism of modeling outputs
– Choice of a specific city (Bordeaux in south-west France);
– Link between data collection, processing and the studied territory’s reality.
Choice of relevant parameters
– From the literature;
– From what urban planners use and look at.
©
UN
20
18
Land-use
Droite courbe tendance population https://population.un.org/wup/Country-Profiles/ Energy consumption Mobility Droite : C:\Users\matthieu.denoux\ownCloud\Code\CalculParametres\input\images\metropole\aire_vegetalisee_pourc.png Deux schémas : C:\Users\matthieu.denoux\ownCloud\Valorisation\2019-05-29_ERSS\poster\infographies.pptx Droite : C:\Users\matthieu.denoux\ownCloud\Code\AffichageIRISEnigma\out_serveur\images\no_legend_recap_bdtopo_bati_union.png and…
• entropy of land use
(Copernicus land cover);
• distance to the closest public
transportation station (bus,
tramway); % road % built land % natural w l A l A block lots A Gauche (retiré) : C:\Users\matthieu.denoux\ownCloud\Code\CalculParametres\input\images\metropole\moyenne_occ_parcelles_non_vides_pourc.png
h
w
d
% %A
n per ageFigure: Five types of neighborhood in Bordeaux, buildings colored according to height using data from IGN BDTOPO
Figure: Green space area according to IGN BDTOPO data
…buildings …land-use Low-tech For example: -Bordeaux's highly dense center -Similar lots of suburbs or smaller towns -Rural areas Ultra-contextual Territorial trends Existing buildings
What matters for urban planners when considering urban evolution? Raw ground Land-use type #2 Land-use type #1 Land-use type #n "Natural" land "Buildable" land "Transport" land
Raw land Land usage Demand
Building type #2 Building type #1 Building type #n Housing demand
Usable land Use of land (buildings) Natural space (various sizes) Road Mobility demand Car Bus Bike High-way Bike paths 𝑣1 𝑣2 𝑣3 𝑣4 𝑣5 𝑣6 Environmentally sensitive Agence Nicolas
Michelin & Associés
Building types Land-use types
Deux images de résultats d’ACP/K-means
C:\Users\matthieu.denoux\ownCloud\Code\CalculParametres\metropole_output\acp\poster_erss_iris_s ols_parcelles_porosite_ecoles
Data Analysis
(PCA, k-means) ‘‘Archetypes’’
To extract characteristics profiles of the existing city, we look, among others,
at…
P
ERSPECTIVES With additional constraints:– Activities
– Mobility demand modes – Public buildings
– Health (cf. World Health Org. recommendations on green spaces)
2. O
UR
OBJECTIVES
© PL U Bo rde au x Métrop ol e– Run the model on all cases – Enhance the archetypes
– Communicate to urban planners (project on a map)
– Compare with other French cities
C:\Users\matthieu.denoux\ownCloud\Code\CautiousTIMESDrawer\resul ts_occupation_sols\20190103007_poster_erss C:\Users\matthieu.denoux\ownCloud\Code\CautiousTIMESDrawer\resul ts_occupation_sols\20190103007_poster_erss C:\Users\matthieu.denoux\ownCloud\Projets\Bordeaux\QGis\Projets\PL U\zones_plu.qgz Incomplete results Possibility to change final demand to correspond to lifestyles, policies or specific scenarios
Figure: Land-use results
(right in Perspectives block: buildings results) Figure: Bordeaux territory by usability
Figure: k-means results on PCA axis
